Quickstart Guide: Bridge Python & Rust with Py03
6Learn how to easily connect Python and Rust code using the pyo3 library for building Python extensions in Rust. This step-by-step walkthrough covers:
Installing requirements: Rust, Python, virtualenv
Creating a virtual environment
Initializing a pyo3 project with maturin
Project structure overview
Building and running the code
Calling Rust functions from Python
Checking in the code with Git
We demo a basic example that sums integers in Rust and calls it from Python. This showcases how straightforward it is to leverage Rust's speed and safety in your Python apps.
The video is ideal for Python developers looking to harness Rust as well as Rustaceans interested in integrating with the Python ecosystem. Everything is done in plain terminal commands with no IDE required.
Hey readers π, if you enjoyed this content, I wanted to share some of my favorite resources to continue your learning journey in technology!
Hands-On Courses for Rust, Data, Cloud, AI and LLMs π
Rust Programming Specialization: https://www.coursera.org/specializations/rust-programming
Rust for DevOps: https://www.coursera.org/learn/rust-for-devops?specialization=rust-programming
Rust LLMOps: https://www.coursera.org/learn/rust-llmops?specialization=rust-programming
Rust Fundamentals: https://www.coursera.org/learn/rust-fundamentals
Data Engineering with Rust: https://www.coursera.org/programs/duke-university-on-coursera-obsio/learn/data-engineering-rust
Python and Rust with Linux Command Line Tools: https://www.coursera.org/learn/python-rust-linux
Virtualization, Docker, and Kubernetes for Data Engineering: https://www.coursera.org/learn/virtualization-docker-kubernetes-data-engineering
Cloud Machine Learning Engineering and MLOps: https://www.coursera.org/learn/cloud-machine-learning-engineering-mlops-duke
MLOps Tools: MLflow and Hugging Face: https://www.coursera.org/learn/mlops-mlflow-huggingface-duke
Data Visualization with Python: https://www.coursera.org/learn/data-visualization-python
Linux and Bash for Data Engineering: https://www.coursera.org/learn/linux-and-bash-for-data-engineering-duke
Spark, Hadoop, and Snowflake for Data Engineering: https://www.coursera.org/learn/spark-hadoop-snowflake-data-engineering
Cloud Virtualization, Containers and APIs: https://www.coursera.org/learn/cloud-virtualization-containers-api-duke
Cloud Data Engineering: https://www.coursera.org/learn/cloud-data-engineering-duke
Python Essentials for MLOps: https://www.coursera.org/learn/python-mlops-duke
DevOps, DataOps, MLOps: https://www.coursera.org/learn/devops-dataops-mlops-duke
Web Applications and Command-Line Tools for Data Engineering: https://www.coursera.org/learn/web-app-command-line-tools-for-data-engineering-duke
MLOps Platforms: Amazon SageMaker and Azure ML: https://www.coursera.org/learn/mlops-aws-azure-duke
Scripting with Python and SQL for Data Engineering: https://www.coursera.org/learn/scripting-with-python-sql-for-data-engineering-duke
Python and Pandas for Data Engineering: https://www.coursera.org/learn/python-and-pandas-for-data-engineering-duke
Cloud Computing Foundations: https://www.coursera.org/learn/cloud-computing-foundations-duke
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